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stridemap_test.cc
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stridemap_test.cc
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// (C) Copyright 2017, Google Inc.
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
// http://www.apache.org/licenses/LICENSE-2.0
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#ifdef INCLUDE_TENSORFLOW
# include <tensorflow/compiler/xla/array2d.h> // for xla::Array2D
#else
# include <array> // std::array
#endif
#include "include_gunit.h"
#include "stridemap.h"
namespace tesseract {
#if !defined(INCLUDE_TENSORFLOW) && 0
namespace xla {
template <typename T>
class Array2D : public std::vector<T> {
public:
Array2D() : std::vector<T>(std::vector<int64_t>{0, 0}) {}
Array2D(const int64_t n1, const int64_t n2) : std::vector<T>(std::vector<int64_t>{n1, n2}) {}
Array2D(const int64_t n1, const int64_t n2, const T value) : std::vector<T>({n1, n2}, value) {}
};
} // namespace xla
#endif
class StridemapTest : public ::testing::Test {
protected:
void SetUp() override {
std::locale::global(std::locale(""));
}
#ifdef INCLUDE_TENSORFLOW
// Sets up an Array2d object of the given size, initialized to increasing
// values starting with start.
std::unique_ptr<xla::Array2D<int>> SetupArray(int ysize, int xsize, int start) {
std::unique_ptr<xla::Array2D<int>> a(new xla::Array2D<int>(ysize, xsize));
int value = start;
for (int y = 0; y < ysize; ++y) {
for (int x = 0; x < xsize; ++x) {
# ifdef INCLUDE_TENSORFLOW
(*a)(y, x) = value++;
# else
a[y][x] = value++;
# endif
}
}
return a;
}
#endif
};
TEST_F(StridemapTest, Indexing) {
// This test verifies that with a batch of arrays of different sizes, the
// iteration index each of them in turn, without going out of bounds.
#ifdef INCLUDE_TENSORFLOW
std::vector<std::unique_ptr<xla::Array2D<int>>> arrays;
arrays.push_back(SetupArray(3, 4, 0));
arrays.push_back(SetupArray(4, 5, 12));
arrays.push_back(SetupArray(4, 4, 32));
arrays.push_back(SetupArray(3, 5, 48));
std::vector<std::pair<int, int>> h_w_sizes;
for (size_t i = 0; i < arrays.size(); ++i) {
h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width());
}
StrideMap stride_map;
stride_map.SetStride(h_w_sizes);
StrideMap::Index index(stride_map);
int pos = 0;
do {
EXPECT_GE(index.t(), pos);
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
pos);
EXPECT_EQ(index.IsLast(FD_BATCH), index.index(FD_BATCH) == arrays.size() - 1);
EXPECT_EQ(index.IsLast(FD_HEIGHT),
index.index(FD_HEIGHT) == arrays[index.index(FD_BATCH)]->height() - 1);
EXPECT_EQ(index.IsLast(FD_WIDTH),
index.index(FD_WIDTH) == arrays[index.index(FD_BATCH)]->width() - 1);
EXPECT_TRUE(index.IsValid());
++pos;
} while (index.Increment());
LOG(INFO) << "pos=" << pos;
index.InitToLast();
do {
--pos;
EXPECT_GE(index.t(), pos);
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
pos);
StrideMap::Index copy(index);
// Since a change in batch index changes the height and width, it isn't
// necessarily true that the position is still valid, even when changing
// to another valid batch index.
if (index.IsLast(FD_BATCH)) {
EXPECT_FALSE(copy.AddOffset(1, FD_BATCH));
}
copy = index;
EXPECT_EQ(index.IsLast(FD_HEIGHT), !copy.AddOffset(1, FD_HEIGHT));
copy = index;
EXPECT_EQ(index.IsLast(FD_WIDTH), !copy.AddOffset(1, FD_WIDTH));
copy = index;
if (index.index(FD_BATCH) == 0) {
EXPECT_FALSE(copy.AddOffset(-1, FD_BATCH));
}
copy = index;
EXPECT_EQ(index.index(FD_HEIGHT) == 0, !copy.AddOffset(-1, FD_HEIGHT));
copy = index;
EXPECT_EQ(index.index(FD_WIDTH) == 0, !copy.AddOffset(-1, FD_WIDTH));
copy = index;
EXPECT_FALSE(copy.AddOffset(10, FD_WIDTH));
copy = index;
EXPECT_FALSE(copy.AddOffset(-10, FD_HEIGHT));
EXPECT_TRUE(index.IsValid());
} while (index.Decrement());
#else
LOG(INFO) << "Skip test because of missing xla::Array2D";
GTEST_SKIP();
#endif
}
TEST_F(StridemapTest, Scaling) {
// This test verifies that with a batch of arrays of different sizes, the
// scaling/reduction functions work as expected.
#ifdef INCLUDE_TENSORFLOW
std::vector<std::unique_ptr<xla::Array2D<int>>> arrays;
arrays.push_back(SetupArray(3, 4, 0)); // 0-11
arrays.push_back(SetupArray(4, 5, 12)); // 12-31
arrays.push_back(SetupArray(4, 4, 32)); // 32-47
arrays.push_back(SetupArray(3, 5, 48)); // 48-62
std::vector<std::pair<int, int>> h_w_sizes;
for (size_t i = 0; i < arrays.size(); ++i) {
h_w_sizes.emplace_back(arrays[i].get()->height(), arrays[i].get()->width());
}
StrideMap stride_map;
stride_map.SetStride(h_w_sizes);
// Scale x by 2, keeping y the same.
std::vector<int> values_x2 = {0, 1, 4, 5, 8, 9, 12, 13, 17, 18, 22, 23, 27, 28,
32, 33, 36, 37, 40, 41, 44, 45, 48, 49, 53, 54, 58, 59};
StrideMap test_map(stride_map);
test_map.ScaleXY(2, 1);
StrideMap::Index index(test_map);
int pos = 0;
do {
int expected_value = values_x2[pos++];
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
expected_value);
} while (index.Increment());
EXPECT_EQ(pos, values_x2.size());
test_map = stride_map;
// Scale y by 2, keeping x the same.
std::vector<int> values_y2 = {0, 1, 2, 3, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,
32, 33, 34, 35, 36, 37, 38, 39, 48, 49, 50, 51, 52};
test_map.ScaleXY(1, 2);
index.InitToFirst();
pos = 0;
do {
int expected_value = values_y2[pos++];
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
expected_value);
} while (index.Increment());
EXPECT_EQ(pos, values_y2.size());
test_map = stride_map;
// Scale x and y by 2.
std::vector<int> values_xy2 = {0, 1, 12, 13, 17, 18, 32, 33, 36, 37, 48, 49};
test_map.ScaleXY(2, 2);
index.InitToFirst();
pos = 0;
do {
int expected_value = values_xy2[pos++];
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
expected_value);
} while (index.Increment());
EXPECT_EQ(pos, values_xy2.size());
test_map = stride_map;
// Reduce Width to 1.
std::vector<int> values_x_to_1 = {0, 4, 8, 12, 17, 22, 27, 32, 36, 40, 44, 48, 53, 58};
test_map.ReduceWidthTo1();
index.InitToFirst();
pos = 0;
do {
int expected_value = values_x_to_1[pos++];
EXPECT_EQ((*arrays.at(index.index(FD_BATCH)))(index.index(FD_HEIGHT), index.index(FD_WIDTH)),
expected_value);
} while (index.Increment());
EXPECT_EQ(pos, values_x_to_1.size());
#else
LOG(INFO) << "Skip test because of missing xla::Array2D";
GTEST_SKIP();
#endif
}
} // namespace tesseract